code: def _from_pretrained(cls, **kwargs):
      config = PretrainedConfig.from_dict(kwargs["config"])
      model = cls(model=torch.nn.Module, config=config)
      return model
  
file_path: optimum/tests/test_modeling_base.py
imports: import os
  import random
  import tempfile
  import unittest
  import requests
  import torch
  from transformers.configuration_utils import PretrainedConfig
  from optimum.modeling_base import OptimizedModel
  from optimum.utils.testing_utils import require_hf_token
label_desc: Use image node_id 2 for calling the DummyModel obj's underlying member method code with example usage: obj._from_pretrained(cls) and returns: model